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» LIDS: Learning Intrusion Detection System
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IMC
2009
ACM
14 years 2 months ago
ANTIDOTE: understanding and defending against poisoning of anomaly detectors
Statistical machine learning techniques have recently garnered increased popularity as a means to improve network design and security. For intrusion detection, such methods build ...
Benjamin I. P. Rubinstein, Blaine Nelson, Ling Hua...
ACSAC
2002
IEEE
14 years 14 days ago
Thirty Years Later: Lessons from the Multics Security Evaluation
Almost thirty years ago a vulnerability assessment of Multics identified significant vulnerabilities, despite the fact that Multics was more secure than other contemporary (and cu...
Paul A. Karger, Roger R. Schell
ICDCS
1999
IEEE
13 years 11 months ago
HiFi: A New Monitoring Architecture for Distributed Systems Management
With the increasing complexity of large-scale distributed (LSD) systems, an efficient monitoring mechanism has become an essential service for improving the performance and reliab...
Ehab S. Al-Shaer, Hussein M. Abdel-Wahab, Kurt Mal...
IJON
2006
146views more  IJON 2006»
13 years 7 months ago
Feature selection and classification using flexible neural tree
The purpose of this research is to develop effective machine learning or data mining techniques based on flexible neural tree FNT. Based on the pre-defined instruction/operator se...
Yuehui Chen, Ajith Abraham, Bo Yang
JMLR
2010
185views more  JMLR 2010»
13 years 2 months ago
HMMPayl: an application of HMM to the analysis of the HTTP Payload
Zero-days attacks are one of the most dangerous threats against computer networks. These, by definition, are attacks never seen before. Thus, defense tools based on a database of ...
Davide Ariu, Giorgio Giacinto